Eitan Borgnia

Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks pdf

Uzi Vishkin, Micah Goldblum, Tom Goldstein, 2021, NeurIPS.

Datasets for Studying Generalization from Easy to Hard Examples

Furong Huang, T. Goldstein, Avi Schwarzschild, 2021, ArXiv.

Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability

Furong Huang, T. Goldstein, Micah Goldblum, 2021, NeurIPS.

Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries

T. Goldstein, Micah Goldblum, Jonas Geiping, 2022, ArXiv.

End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking

Furong Huang, T. Goldstein, Avi Schwarzschild, 2022, ArXiv.

Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise

Furong Huang, T. Goldstein, Micah Goldblum, 2022, NeurIPS.

What do Vision Transformers Learn? A Visual Exploration

Micah Goldblum, T. Goldstein, Manli Shu, 2022, arXiv.org.

Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff pdf

Jonas Geiping, Micah Goldblum, Liam Fowl, 2020, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations

Furong Huang, T. Goldstein, Micah Goldblum, 2021, ArXiv.

Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries

T. Goldstein, Micah Goldblum, Jonas Geiping, 2022, ArXiv.

Modulation of MICAL Monooxygenase Activity by its Calponin Homology Domain: Structural and Mechanistic Insights

L. Amzel, M. Bianchet, M. Urquiza, 2016, Scientific Reports.